Corn stigma ameliorates hyperglycemia in zebrafish and GK rats of type 2 diabetes

Corn stigma (CS), derived from the stigma and style of gramineous plant Zea mays. The medicinal use of CS can be traced back to Dian Nan Materia Medica. Lingnan Medicinal Plants Compendium records its effectiveness in ameliorating diabetes. Diabetes is a metabolic disorder characterized by hyperglycemia and the consequent chronic complications of kidney, heart, brain and other organs, which pose a significant threat to human health. CS has shown great potential in relieving hyperglycemia associated with diabetes. However, the mechanism of CS in treating diabetes remains unclear. To explore the pathogenesis of diabetes and the mechanism of CS improving hyperglycemia in diabetes. We measured apigenin and luteolin contents in CS by UPLC/MS/MS method. Selecting Wistar rats as normal group, and GK rats as model group. For rats, we detected glucose and lipid metabolism indicators, including GHb, AST, ALT, U-Glu, UA, U-TP, U-ALB, and ACR after treatment. For zebrafish, we utilized alloxan and sucrose to establish the diabetes model. Measuring zebrafish blood glucose is employed to evaluate the hypoglycemic capability of CS. In order to explore the mechanism of CS in treating diabetes, we sequenced the transcriptome of zebrafish, compared differentially expressed genes of normal, diabetic, and CS-treated group, and validated multiple enrichment pathways by PCR. CS can improve blood glucose levels in both GK rats and diabetic zebrafish. For rats, CS partially restored glucose and lipid metabolism indicators. Transcriptome data from zebrafish showed a close correlation with steroid biosynthesis. The RNA-Sequencing was consistent with PCR results, indicating that CS downregulated gene (fdft1, lss, cyp51) expression concerned with steroid biosynthesis pathway in the diabetes model. CS effectively improved blood glucose levels, regulated glucose and lipid metabolism by suppressing gene expression in steroid biosynthesis pathway, and ameliorated hyperglycemia. Our research provides valuable insights for CS in the treatment of diabetes, and proposes a new strategy for selecting clinical medications for diabetes.